Title: "Seeing
Myself in the Dark: Interactions between Vision and Proprioception
Reveal an Extended Sense of 'me'."Abstract:
Effectively interacting with our environment requires a multimodal sense
of the body, the putative “body schema”. Extending this sense of the
body beyond the physical body can lead to improvements in efficiency, as
evidenced by salmon and trout exploiting vortices in rivers, and new
capabilities, exemplified by tool use in humans. The notion of an
extended sense of the body has been the topic of philosophical
discussion for more than a century. Only recently has it been subject to
empirical testing. In this talk, I will present a series of experiments
that examine if, and under what conditions, our body sense can be
extended. The first set of experiments investigated the cognitive
factors that support the integration of visual and proprioceptive
information into the body schema. Our experiments show that that a sense
of perceived ownership is critical. A second set of experiments
explicitly tested if external objects can be integrated into the body
schema. We found that without any experience or training objects can be
quickly incorporated into the body schema, but also that these
extensions have limitations. In particular, we found that second-order
extensions of the body schema, using tools to interact with objects,
were not possible. This suggests that physical contact plays a role in
assimilating objects. A third series of experiments examined the
relationship between the body schema and self-awareness. These
experiments examined the possibility that passing the so-called mirror
test – a test for self-awareness that only a few species with
higher-order cognitive abilities have passed (e.g. humans and dolphins)
– may be mediated by an extended body sense. Our experiments found
support of this notion by showing that humans maintain a bodily
connection to our reflections in the mirror. This result in conjunction
with our findings that perceived ownership mediates the integration of
visual and proprioceptive information suggests that success in passing
the mirror test may be derived from a sense of ownership over our
reflection in the mirror.

Title: "Making
Sense of Others’ Actions: Psychological Reasoning in Infancy."Abstract:
Beginning early in the first year of life, infants attempt to make sense
of others’ intentional actions. Although the nature and development of
infants’ psychological reasoning (or “theory of mind”, as it is
sometimes called) remain the subjects of intense controversy, the notion
that infants already possess some understanding of others’ actions is
becoming widely accepted. In much of the research on this topic, infants
watch simple scenes in which an agent acts on objects (e.g., a person
reaches consistently for chocolates as opposed to carrots).
Investigators examine what mental states infants attribute to the agent,
and how they use these mental states to interpret and predict the
agent’s actions. Results indicate that infants in the first year of life
are able to attribute at least two kinds of mental states to an agent:
motivational states (e.g., goals, dispositions), which specify
the agent’s motivation in the scene, and reality-congruent
informational states (e.g., knowledge, ignorance), which specify
what accurate information the agent possesses or lacks about the scene.
Over the past few years, experiments on reality-incongruent
informational states have focused on the question of whether infants
also realize that an agent can hold false or pretend beliefs about a
scene. In my talk, I will review evidence that, when attempting to make
sense of an agent’s actions in a simple scene, infants take into account
the agent's motivational, reality-congruent informational, and
reality-incongruent informational states.

Title: "Metacognition of Agency:
Brain Monitoring of Control"Abstract: The
question addressed by this research is how does a person know that he or
she is the agent? According to many, having the metaknowledge that one
is, oneself, the actor (or the thinker) is simply a given. It is direct
knowledge. This is what Ryle called the “Official Doctrine”. Descartes
believed that this was, in fact, the only sure knowledge and based his
entire epistemological system upon it. In contrast to this view, I will
take the position that people's knowledge about their own agency is
inferential , like other metacognitive judgments. All researchers in
metacognition agree that all metacognitive judgments that have been
studied to date are based on cues. So, we can look for cues that feed
into the metacognitive judgments of agency, investigating both their
behavioral profiles and their brain prints. Additionally, given that
metacognitions of agency are based on cues, we also investigate
individual differences, age differences and mistakes that people make in
their knowledge of when they are the agent.

Title: "Constraints and
Flexibility as Hallmarks of Early Object Representations"Abstract:
A central focus of cognitive psychology is: What is the format of the
mental representations that store information, and what computations can
be performed over those representations? Here I explore answers to these
questions for the case of the concept "individual," drawing from work on
object cognition, working memory, and cognitive development. I build a
case that representations of individuals (e.g., “object”) are in some
ways strikingly constrained by the architecture of working memory. At
the same time, the variety of computations that can be performed over
these representations allow for great representational flexibility. For
example, although the canonical individual may be an object, multiple
objects may be bound into sets which then function as an individual for
the purposes of attention and memory. This is true starting in infancy.
The emerging portrait is one of continuity across the lifespan, with
both infants and adults making use of a representational system that is
at once both remarkably limited and surprisingly flexible.

Title: "How to Grow
a Mind: Statistics, Structure, and Abstraction"Abstract: How do humans come to know so much about the
world from so little data? From sparse and noisy fragments of
experience, we draw generalizations that successfully guide our actions
in future situations and tasks we have never faced before. Even young
children can infer the meanings of words, the hidden properties of
objects, or the existence of causal relations from just one or a few
relevant observations -- far outstripping the capabilities of
conventional learning machines. How do they do it? And how can we
bring machines closer to these human-like learning abilities?
These questions are instances of the
classic "problem of induction", and they have a classic answer. Rich
sources of prior knowledge must be available to constrain human
learners' hypothesis spaces and enable meaningful generalizations. In
this talk I will describe some attempts to capture and study this
insight more formally in computational theories of cognition. I will
argue that to understand the nature, use and origins of knowledge
guiding human inferences, we need to bring together several ideas that
are familiar to cognitive scientists but are traditionally viewed more
as competitors rather than as complementary pieces of the puzzle. These
ideas are statistics, structure, and abstraction. By "statistics", I
mean specifically Bayesian inference in probabilistic generative models.
The hypothesis spaces and priors of Bayesian learning provide a natural
language in which to describe the inductive biases that guide human
generalization. Formalizing these inductive biases, these
knowledge-based Bayesian priors, will require us to define probabilistic
models over structured symbolic representations such as graphs,
grammars, predicate logic, schemas, theories or programs. To explain
the origins of these priors, we will adopt a hierarchical Bayesian
framework. Inference occurs in parallel at multiple levels of
abstraction, allowing the knowledge that serves as background or
inductive constraints for one level of learning to itself be generalized
from experience, via simultaneous inferences occurring at higher levels
of the hierarchy.
More specifically, this talk will
focus on models of learning and "learning to learn" about categories,
word meanings and causal relations. I will show in each of these
settings how human learners might balance the need for strongly
constraining inductive biases -- necessary for rapid generalization --
with the flexibility to adapt to the structure of new environments,
learning new inductive biases for which our minds could not have been
pre-programmed. I will also discuss briefly how this approach extends
to richer forms of knowledge, such as intuitive psychological and social
inference, physical reasoning and natural number.

Title: "Predicting
Actions and Outcomes in Infancy."Abstract:
The ability to form on-line predictions about the likely outcomes
of ongoing events is a prerequisite for a number of social cognitive
abilities, including coordinating one's actions with others, the basis
of our human ability to cooperate with one another. Although cooperation
and collaboration are hypothesized to be defining features of human
ontogeny, it was unclear whether human infants had the prerequisite
ability to generate predictions concerning others' actions. In this
talk, I will present both behavioral and neuroimaging data from infants
suggesting that indeed this ability is present in the first year of
life, and I will discuss potential cognitive and neural mechanisms that
may be recruited in support of this ability.

May 6 —
Jeff Heinz (Linguistics
and Cognitive Science, University of Delaware)

Title: "Modular
Phonological Learning."Abstract:
Debates between domain-specific (Gallistel 1999) and
domain-general (Marescal et. al 2007, Spencer et. al 2009) learning
strategies often focus on the possible existence of a module specialized
for speech and language (Liberman 1996). This talk argues that within
the domain of language itself there are specialized learning mechanisms.
In particular, formal language-theoretic and formal learning-theoretic
analyses of the sound patterns in the world's languages imply three
different learning mechanisms. Additionally, a broad interdisciplinary
research program for investigating this hypothesis is outlined, and
recent relevant results are discussed.